In general humans have five senses, among all vision is the most important and best gift given to the humans by GOD, but it is limited to some of the people due to their Visual Impairment issues. If vision is the problem then GOD will give the capabilities in other senses. The proportion of visually impaired and blind people in the overall world has become a very large. In a survey report given by WHO (World Health Organization) in 2010, they estimated nearly 285.389 million people are suffering with visual impairment problems across the globe. Many equipment’s (Ex: Cane, Assistive shoe, Spectacles) are developed by different authors for detection of obstacles by visual impaired people over the time. All these equipment’s are developed by using different techniques like IoT enabled smart cane, GPS/GSM based smart cane, Wearable devices like Assistive shoe’s and blind vision spectacles which detects the obstacles, Smart Phone based navigation technology , Image processing techniques based smart cane which uses the camera for capturing the images, ETA’s (Electronic Travel Aid’s), normal Ultrasonic sensor based smart canes, Sensors(Ultrasonic, LDR’s, Soil moisture and water detection) used smart cane and the most advanced smart canes which uses the Algorithms of Machine Learning and Deep Learning ANN, CNN, RNN. In this paper, we present a clear survey of the navigation systems of blind/Visual impaired people that are proposed by different authors highlighting various technologies used, designs implemented, working challenges faced and requirements of blind people for their autonomous navigation either in indoor or outdoor environment. Also we aims at presenting several existing literatures which are based on object detection by blind people. Due to the advancement in techniques and technology, study, analysis and evaluation of all these proposals by different authors will play a vital role. Hence this survey will concentrate on analyzing the process involved in detection of obstacles with different techniques.3

Visual Impairment, IoT, Ultrasonic sensor, wearable devices, Image processing, smart phone, LDR (Light Dependent Resistor), Machine Learning, Deep Learning

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